Composing Verifiable Conceptual Models via Building Blocks: Towards Design-Time Verification of Agentic AI Workflows

2026-06-19

AI Summary

This work addresses the lack of structural correctness verification during the design phase in existing AI agent workflow platforms, which typically rely on runtime safeguards. The authors propose a workflow modeling approach centered on reusable building blocks and introduce, for the first time, a set of twelve structural rules. By leveraging graph-based representations and a rule engine, the method enables static, formal checks for compatibility and logical consistency at design time. Experimental evaluation demonstrates that the prototype system efficiently detects design violations on a dataset comprising 48 defective workflows and 168 structural variants, maintaining high detection accuracy even when tasks are split across multiple agents. This significantly enhances the reliability and maintainability of workflow designs.

Abstract

Agentic AI systems orchestrate multiple LLM-based agents through workflow architectures that coordinate decisions, tools, and external actions. While current platforms emphasize runtime safeguards, little support exists for verifying workflows during system design. From a Modeling \& Simulation perspective, this gap is analogous to composing conceptual models without verifying whether their building blocks interact coherently. We propose a design-time verification approach that models agentic workflows as compositions of reusable building blocks and checks their compatibility through twelve structural rules. We implemented these rules in a software prototype and evaluated them using two openly released datasets: 48 workflows with known design flaws and 168 variants that preserve workflow logic but alter graph structure. Results show that our verifier reliably detects violations even when flawed designs are obscured through structural transformations such as splitting tasks between agents. Future works could combine our verification with community repositories of building blocks to compose safe agentic workflows.

Problem

• Agentic AI
• Design-Time Verification
• Workflow Composition
• Conceptual Models
• Building Blocks

Innovation

• design-time verification
• agentic AI workflows
• building blocks
• structural rules
• conceptual modeling